Literature DB >> 11420367

The yeast protein interaction network evolves rapidly and contains few redundant duplicate genes.

A Wagner1.   

Abstract

In this paper, the structure and evolution of the protein interaction network of the yeast Saccharomyces cerevisiae is analyzed. The network is viewed as a graph whose nodes correspond to proteins. Two proteins are connected by an edge if they interact. The network resembles a random graph in that it consists of many small subnets (groups of proteins that interact with each other but do not interact with any other protein) and one large connected subnet comprising more than half of all interacting proteins. The number of interactions per protein appears to follow a power law distribution. Within approximately 200 Myr after a duplication, the products of duplicate genes become almost equally likely to (1) have common protein interaction partners and (2) be part of the same subnetwork as two proteins chosen at random from within the network. This indicates that the persistence of redundant interaction partners is the exception rather than the rule. After gene duplication, the likelihood that an interaction gets lost exceeds 2.2 x 10(-3)/Myr. New interactions are estimated to evolve at a rate that is approximately three orders of magnitude smaller. Every 300 Myr, as many as half of all interactions may be replaced by new interactions.

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Year:  2001        PMID: 11420367     DOI: 10.1093/oxfordjournals.molbev.a003913

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


  123 in total

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4.  Evolution of the yeast protein interaction network.

Authors:  Hong Qin; Henry H S Lu; Wei B Wu; Wen-Hsiung Li
Journal:  Proc Natl Acad Sci U S A       Date:  2003-10-13       Impact factor: 11.205

5.  Evolution and topology in the yeast protein interaction network.

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6.  Molecular evolution in large genetic networks: does connectivity equal constraint?

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Authors:  Gavin C Conant; Andreas Wagner
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Review 8.  Network analysis of GWAS data.

Authors:  Mark D M Leiserson; Jonathan V Eldridge; Sohini Ramachandran; Benjamin J Raphael
Journal:  Curr Opin Genet Dev       Date:  2013-11-26       Impact factor: 5.578

9.  How the global structure of protein interaction networks evolves.

Authors:  Andreas Wagner
Journal:  Proc Biol Sci       Date:  2003-03-07       Impact factor: 5.349

10.  A gene regulatory network model for cell-fate determination during Arabidopsis thaliana flower development that is robust and recovers experimental gene expression profiles.

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